51 citations · 74 across the 8 of their papers we have counts for
9 papers
Designing Strongly Correlated Quantum Phases of Matter with Foundation Neural-Network Quantum States
Alessandro Sinibaldi, Luciano Loris Viteritti, Riccardo Rende +2
Materials design is an inverse problem: finding the couplings of a microscopic Hamiltonian whose ground state exhibits a desired property. For strongly correlated quantum systems,…
Thermalization Dynamics in the Two-Dimensional Hubbard Model with Neural-Network Quantum States
Alessandro Sinibaldi, Luciano Loris Viteritti, Riccardo Rende +2
Thermalization in strongly correlated fermionic systems remains a central open problem in quantum many-body physics. In this work, we investigate the real-time dynamics and the app…
Scaling Laws for Neural-Network Quantum States
Riccardo Rende, Alessandro Sinibaldi, Luciano Loris Viteritti +3
Scaling laws, the power-law relations between loss, architecture size, and compute observed in modern neural networks, offer a quantitative way to characterize the complexity of a…
Grassmann Variational Monte Carlo with neural wave functions
Douglas Hendry, Alessandro Sinibaldi, Giuseppe Carleo
Excited states play a central role in determining the physical properties of quantum matter, yet their accurate computation in many-body systems remains a formidable challenge for…
Non-stabilizerness of Neural Quantum States
Alessandro Sinibaldi, Antonio Francesco Mello, Mario Collura +1
We introduce a methodology to estimate non-stabilizerness or "magic", a key resource for quantum complexity, with Neural Quantum States (NQS). Our framework relies on two schemes b…
Time-dependent Neural Galerkin Method for Quantum Dynamics
Alessandro Sinibaldi, Douglas Hendry, Filippo Vicentini +1
We introduce a classical computational method for quantum dynamics that relies on a global-in-time variational principle. Unlike conventional time-stepping approaches, our scheme c…
Comment on "Can Neural Quantum States Learn Volume-Law Ground States?"
Zakari Denis, Alessandro Sinibaldi, Giuseppe Carleo
Passetti et al. [Physical Review Letters 131, 036502 (2023)] recently assessed the potential of neural quantum states (NQS) in learning ground-state wave functions with volume-law…
Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution
Alessandro Sinibaldi, Clemens Giuliani, Giuseppe Carleo +1
We analyze the accuracy and sample complexity of variational Monte Carlo approaches to simulate the dynamics of many-body quantum systems classically. By systematically studying th…
A New Scale-Dependent Cosmology with the Generalized Robertson--Walker Metric and Einstein Equation
C. W. Kim, A. Sinibaldi, J. Song
Based on the observed increase of as a function of cosmic scale, the Robertson--Walker metric and the Einstein equation are generalized so that , , and the age of…